Bayesian EEG source localization using a structured sparsity prior

@article{Costa2017BayesianES,
  title={Bayesian EEG source localization using a structured sparsity prior},
  author={Facundo Costa and Hadj Batatia and Thomas Oberlin and Carlos D'Giano and Jean-Yves Tourneret},
  journal={NeuroImage},
  year={2017},
  volume={144},
  pages={142-152}
}
This paper deals with EEG source localization. The aim is to perform spatially coherent focal localization and recover temporal EEG waveforms, which can be useful in certain clinical applications. A new hierarchical Bayesian model is proposed with a multivariate Bernoulli Laplacian structured sparsity prior for brain activity. This distribution approximates a mixed ℓ20 pseudo norm regularization in a Bayesian framework. A partially collapsed Gibbs sampler is proposed to draw samples… CONTINUE READING
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